Meeting Title: Analysis Planning Session Date: 2024-08-12 Meeting participants: Jakob Kagel, Nicolas Sucari
WEBVTT
1 00:02:53.160 ⇒ 00:02:54.380 Jakob Kagel: Hey? How’s it going.
2 00:02:56.810 ⇒ 00:02:58.729 Nicolas Sucari: Hey, Jacob, how are you?
3 00:02:59.000 ⇒ 00:03:01.200 Jakob Kagel: Doing well doing? Well, how about yourself?
4 00:03:01.780 ⇒ 00:03:02.750 Nicolas Sucari: All good.
5 00:03:05.160 ⇒ 00:03:10.019 Nicolas Sucari: I don’t know if Utam is gonna join today. He was traveling back to Texas. I think.
6 00:03:10.360 ⇒ 00:03:11.719 Jakob Kagel: Yeah. No worries.
7 00:03:12.960 ⇒ 00:03:20.470 Nicolas Sucari: Yeah, I don’t know if we have a lot of things to do king was asking for that customer acquisition cost.
8 00:03:20.470 ⇒ 00:03:24.120 Jakob Kagel: Right. I just wanted to ask about that real quick. Yeah. Sorry.
9 00:03:24.640 ⇒ 00:03:31.889 Nicolas Sucari: I don’t think we have the measure anywhere in in real I I mean, we need to work on that, I think.
10 00:03:33.330 ⇒ 00:03:35.290 Nicolas Sucari: but I don’t know. Do you have any other information.
11 00:03:35.290 ⇒ 00:03:45.529 Jakob Kagel: Yeah, let’s just talk about it real quick, because I think we can knock it out pretty quick, and it’ll be an easy win. But I just want to make sure that you know we give her like what she’s looking for. So
12 00:03:45.880 ⇒ 00:03:54.719 Jakob Kagel: you’re saying, that basically like that. She’s looking for customer acquisition cost, like, by the channel. Right?
13 00:03:54.740 ⇒ 00:03:55.750 Jakob Kagel: Yeah.
14 00:03:56.320 ⇒ 00:03:57.580 Jakob Kagel: So
15 00:03:58.530 ⇒ 00:04:00.120 Jakob Kagel: I guess, like.
16 00:04:01.240 ⇒ 00:04:18.790 Jakob Kagel: the thing is like, we have to be able to tie the acquisition to the Channel, and I’m not sure that we have that now. I will look into this and try to figure it out, but I’m pretty sure like the only way that we could determine acquisition right now would just be to say, like from first, st like purchase date.
17 00:04:19.079 ⇒ 00:04:33.232 Jakob Kagel: like anybody who make a purchase like if you if you didn’t make a purchase in 2023 or whatever, and if you didn’t make a purchase in the last month, and you made your 1st purchase in the next month. Then you’re, you know, acquired
18 00:04:33.540 ⇒ 00:04:37.299 Nicolas Sucari: But how do you? How do you match, like the
19 00:04:37.550 ⇒ 00:04:40.229 Nicolas Sucari: the actual purchase with the campaign.
20 00:04:40.830 ⇒ 00:04:43.610 Jakob Kagel: That’s what I’m saying. I don’t know if we well, I mean
21 00:04:43.920 ⇒ 00:05:09.850 Jakob Kagel: we can do, I mean, in certain situations, like, if we talk about like Clavio, right? Like email or whatever it’s like, we can take everybody who got the email like in a certain in the certain time range. But the thing is like if we’re only like, I don’t know if they’re only targeting like our existing customers for those kind of outreach I mean, I know, we talked about the scraping and potentially, you know.
22 00:05:09.850 ⇒ 00:05:28.969 Jakob Kagel: targeting some of like, yeah, you know, scraped listings. And in that case, it’s like, yeah, if you have a list of all the emails you know that the campaign went to. And then you can see, okay, at the whatever the start date of the campaign, and then who all made a purchase, you know, in the the duration of the campaign.
23 00:05:28.970 ⇒ 00:05:44.030 Nicolas Sucari: Yeah. But okay, yeah, I get it. I get it like, that’s for new customers. I think we can do that. But for what we have now like, if you wanna get like, what is the this? This measure for the actual campaigns and the actual like
24 00:05:44.110 ⇒ 00:05:58.189 Nicolas Sucari: sales that they are having like. Can’t we track like one campaign and see their its conversions and see but we we cannot match that conversions of clicks into purchases right like we don’t have any anything to match that.
25 00:05:58.550 ⇒ 00:06:02.780 Jakob Kagel: Let me. Here, let’s look at it right now, real quick, just
26 00:06:02.930 ⇒ 00:06:03.660 Jakob Kagel: it’s just.
27 00:06:03.660 ⇒ 00:06:04.529 Nicolas Sucari: Yeah, for me.
28 00:06:04.530 ⇒ 00:06:06.240 Jakob Kagel: 10 min, but let’s just there
29 00:06:06.610 ⇒ 00:06:10.763 Jakob Kagel: up, and we can just look at it on while we’re on the call.
30 00:06:11.220 ⇒ 00:06:24.129 Nicolas Sucari: She asked me about that paid marketing performance dashboard that we have, but that is like only like the how, how the conversion how the campaigns went like if there were clicks and we count
31 00:06:24.670 ⇒ 00:06:29.529 Nicolas Sucari: versions right? But would that mean that they actually purchased.
32 00:06:30.410 ⇒ 00:06:32.610 Jakob Kagel: Is that dashboard is in
33 00:06:33.050 ⇒ 00:06:34.950 Nicolas Sucari: No, really, yeah.
34 00:06:35.280 ⇒ 00:06:36.360 Jakob Kagel: Okay.
35 00:06:36.790 ⇒ 00:06:42.969 Jakob Kagel: here, let’s here. Let’s pull that one up first, st maybe real quick, cause I just want to take a look at that and see?
36 00:06:43.723 ⇒ 00:06:46.130 Jakob Kagel: One second, I’m gonna share my screen.
37 00:06:46.360 ⇒ 00:06:47.060 Nicolas Sucari: Right.
38 00:06:53.070 ⇒ 00:06:56.630 Nicolas Sucari: because we have a conversion rate there. But like
39 00:06:58.010 ⇒ 00:06:59.050 Nicolas Sucari: I don’t know.
40 00:06:59.240 ⇒ 00:07:02.120 Jakob Kagel: Hold on. I’m sharing my screen one second.
41 00:07:04.140 ⇒ 00:07:05.809 Jakob Kagel: Okay, you can see my screen.
42 00:07:06.150 ⇒ 00:07:06.790 Nicolas Sucari: Yep.
43 00:07:07.110 ⇒ 00:07:09.499 Jakob Kagel: Okay. So which one is it? It’s the.
44 00:07:09.780 ⇒ 00:07:11.730 Nicolas Sucari: Paid paid marketing, performance.
45 00:07:11.730 ⇒ 00:07:13.839 Jakob Kagel: Paid marketing performance. Okay.
46 00:07:14.660 ⇒ 00:07:18.249 Jakob Kagel: alright. So yeah, we have campaign id.
47 00:07:18.800 ⇒ 00:07:23.430 Jakob Kagel: and then we have impressions and we have conversion rate. But yes, so this is
48 00:07:23.860 ⇒ 00:07:27.709 Jakob Kagel: basically, how is this calculated? Do we know you’re saying.
49 00:07:27.710 ⇒ 00:07:33.460 Nicolas Sucari: Yeah, I I want to check that. Let me open visual studio for a minute.
50 00:07:33.460 ⇒ 00:07:34.660 Jakob Kagel: Yeah. No worries.
51 00:07:37.650 ⇒ 00:07:40.519 Nicolas Sucari: Real dashboard. This is
52 00:07:41.140 ⇒ 00:07:45.650 Nicolas Sucari: marketing performance. This is
53 00:07:46.060 ⇒ 00:07:52.220 Nicolas Sucari: so. The conversion rate is impressions over clicks. Yeah.
54 00:07:52.220 ⇒ 00:07:54.748 Jakob Kagel: Questions over clicks. Okay,
55 00:07:56.180 ⇒ 00:07:57.440 Jakob Kagel: okay.
56 00:07:57.900 ⇒ 00:08:04.479 Jakob Kagel: so right, okay, so we have cost of the problem here. It looks like, yes, like.
57 00:08:04.540 ⇒ 00:08:22.611 Jakob Kagel: we don’t have anything that we can tie this back to like a specific person. And we don’t have like, even we actually don’t need to tie back to a specific person, but we would have to have, like the purchase amount, like of the from the people that
58 00:08:22.980 ⇒ 00:08:33.309 Nicolas Sucari: Yeah, we we don’t. We don’t need to like get the list of emails or the actual people that click there. We just need to understand if we can get which
59 00:08:33.620 ⇒ 00:08:39.910 Nicolas Sucari: sales came through these clicks right? And then we can match like.
60 00:08:40.470 ⇒ 00:08:44.590 Nicolas Sucari: yeah, those sales against all the spends on this campaign.
61 00:08:45.660 ⇒ 00:08:51.399 Jakob Kagel: Yeah, I mean, I assume conversions here also is not purchases. I assume it’s.
62 00:08:51.400 ⇒ 00:08:57.430 Nicolas Sucari: Exactly conversions, no conversions. I I have it right here. Conversions is
63 00:08:58.015 ⇒ 00:08:59.649 Nicolas Sucari: let me see.
64 00:08:59.710 ⇒ 00:09:06.519 Nicolas Sucari: So we have the conversion rate. These impressions over clicks and conversions. Where do we have that.
65 00:09:08.940 ⇒ 00:09:11.419 Jakob Kagel: This is for Google adwords table, yeah.
66 00:09:13.940 ⇒ 00:09:15.329 Nicolas Sucari: Okay, right?
67 00:09:15.780 ⇒ 00:09:19.530 Nicolas Sucari: Or is this getting combined marketing performance model?
68 00:09:22.590 ⇒ 00:09:26.420 Nicolas Sucari: Okay? Yeah, no. We have clicks. And yeah, that converts.
69 00:09:34.060 ⇒ 00:09:39.240 Nicolas Sucari: So we have conversions for what? What do you have there? No, we don’t have conversions, or yes.
70 00:09:39.240 ⇒ 00:09:45.050 Jakob Kagel: I’m just looking in Google adwords table. I mean what we can give her. This is like.
71 00:09:45.620 ⇒ 00:09:53.570 Jakob Kagel: not exactly what she’s asking for, but I think it’s maybe like close enough, or like, well, at least
72 00:09:53.630 ⇒ 00:09:56.070 Jakob Kagel: is we can just give her cost per click.
73 00:09:56.960 ⇒ 00:09:59.820 Nicolas Sucari: But they already. I think it’s already.
74 00:09:59.820 ⇒ 00:10:00.930 Jakob Kagel: Okay.
75 00:10:00.930 ⇒ 00:10:05.460 Nicolas Sucari: That’s already in the yeah. It’s already in the in the dashboard cost per click.
76 00:10:05.870 ⇒ 00:10:06.930 Jakob Kagel: Okay.
77 00:10:07.990 ⇒ 00:10:17.649 Nicolas Sucari: She wants to know. Yeah, the the that new measure so that he can. They can understand in which channel is like more.
78 00:10:17.880 ⇒ 00:10:18.840 Nicolas Sucari: and then I’ll
79 00:10:19.230 ⇒ 00:10:30.040 Nicolas Sucari: they can spend more so that they can get more probably. But yeah, I don’t know if we have the conversions on the Facebook ones. But if we have on the Google one, we can just take a look at that one.
80 00:10:30.040 ⇒ 00:10:30.800 Jakob Kagel: I’m trying to.
81 00:10:30.800 ⇒ 00:10:32.200 Nicolas Sucari: Calculating.
82 00:10:32.200 ⇒ 00:10:41.120 Jakob Kagel: Still like conversions here is still, I mean we I don’t. I don’t know. I’m just saying, but this is still clicks right over impressions, right or no.
83 00:10:41.360 ⇒ 00:10:43.279 Nicolas Sucari: I don’t know. Let me see.
84 00:10:43.280 ⇒ 00:10:44.050 Jakob Kagel: Yeah, she.
85 00:10:44.050 ⇒ 00:10:45.560 Nicolas Sucari: Google adwords.
86 00:10:56.490 ⇒ 00:11:02.589 Jakob Kagel: Cause, even if we have conversions here as like purchases that we still don’t know the total purchase amount.
87 00:11:02.590 ⇒ 00:11:05.250 Nicolas Sucari: We have the conversions from the ads.
88 00:11:05.895 ⇒ 00:11:07.199 Nicolas Sucari: Let me see.
89 00:11:09.160 ⇒ 00:11:21.619 Jakob Kagel: But I guess we could say we don’t need the actual, the purchase amount because we have the cost. So we just need the cost divided by the number of conversions. If if conversions is a purchase to do, customer, acquisition costs.
90 00:11:23.070 ⇒ 00:11:24.620 Nicolas Sucari: Yeah, probably
91 00:11:24.920 ⇒ 00:11:28.999 Nicolas Sucari: we have something that’s called conversion value on.
92 00:11:30.210 ⇒ 00:11:31.730 Nicolas Sucari: Let me see
93 00:11:32.310 ⇒ 00:11:35.059 Nicolas Sucari: on that. I think on that table.
94 00:11:36.150 ⇒ 00:11:37.230 Jakob Kagel: In this one.
95 00:11:37.530 ⇒ 00:11:41.040 Nicolas Sucari: In station, looking at station.
96 00:11:41.040 ⇒ 00:11:43.710 Jakob Kagel: Oh, here it is. Conversions. Value. Yeah.
97 00:11:43.710 ⇒ 00:11:46.710 Nicolas Sucari: Probably we need to take a look at that one from Google right?
98 00:11:47.100 ⇒ 00:11:54.629 Jakob Kagel: Right? Exactly. I mean, she asked. I mean, yeah, you’re saying specifically that she’s interested in Facebook and Google. So maybe we can use these tables.
99 00:11:54.960 ⇒ 00:11:56.270 Nicolas Sucari: Yeah, exactly.
100 00:11:57.500 ⇒ 00:12:02.270 Jakob Kagel: We just need to know the definition of the these columns. That’s all. Yeah.
101 00:12:02.940 ⇒ 00:12:09.130 Nicolas Sucari: Yeah, I I can take a look on on the code and see if we can.
102 00:12:09.840 ⇒ 00:12:20.156 Nicolas Sucari: We can understand that one. But yeah, I mean, if we have the what they are spending on like a Google campaign, a specific Google campaign. And we can then,
103 00:12:20.760 ⇒ 00:12:31.079 Nicolas Sucari: have these conversions value of each of those campaigns. I think we can calculate, because the cost of acquisition for each of the each of that campaigns right.
104 00:12:31.270 ⇒ 00:12:35.150 Jakob Kagel: Yeah, I mean, let’s just I mean, if you don’t mind, let’s just look at it right now, like.
105 00:12:35.150 ⇒ 00:12:35.540 Nicolas Sucari: Guy, yeah.
106 00:12:35.540 ⇒ 00:12:41.120 Jakob Kagel: I don’t know if you know where to find the definition. That’s the part I don’t know is exactly where to find the the definition.
107 00:12:41.120 ⇒ 00:12:45.019 Nicolas Sucari: Version value. Let me try. I’m gonna try to look at that in the code. Yeah.
108 00:12:45.020 ⇒ 00:12:49.760 Jakob Kagel: Is it? I mean? What is the best place to look? Is it like an elementary or something? Or where is it.
109 00:12:49.760 ⇒ 00:12:53.059 Nicolas Sucari: Oh, I go directly to the code
110 00:12:53.270 ⇒ 00:12:56.420 Nicolas Sucari: and try to see how all of that is
111 00:12:56.720 ⇒ 00:12:57.640 Nicolas Sucari: done
112 00:12:57.870 ⇒ 00:12:58.770 Nicolas Sucari: right.
113 00:12:58.770 ⇒ 00:13:05.910 Jakob Kagel: And this looks like conversions. Value looks like it would be a sales number, but we still should validate it. Yeah.
114 00:13:10.960 ⇒ 00:13:13.779 Jakob Kagel: But yeah, if you. If you are in Github.
115 00:13:17.320 ⇒ 00:13:20.219 Jakob Kagel: I mean, this looks like it would be sales. Yeah.
116 00:13:22.380 ⇒ 00:13:24.480 Nicolas Sucari: Yeah, I think it’s it’s that one right?
117 00:13:25.740 ⇒ 00:13:26.850 Jakob Kagel: Which one.
118 00:13:27.110 ⇒ 00:13:40.149 Nicolas Sucari: Like like if we if we have that Google sorry that conversions value from Google. And then, yeah, exactly say, each of those campaign ids. Why, why do we have repeated ones.
119 00:13:40.150 ⇒ 00:13:45.849 Jakob Kagel: Well, because some of these, I mean, these are all like separate interactions, like people would have like an interaction.
120 00:13:45.850 ⇒ 00:13:48.659 Nicolas Sucari: Can you? Yeah, can you group by campaign? Id.
121 00:13:48.660 ⇒ 00:13:52.609 Jakob Kagel: Yeah, I can group Bob, but I think like it might be better if we look at like
122 00:13:53.266 ⇒ 00:13:58.550 Jakob Kagel: like ad id. And like some other fields here, like, just broken out.
123 00:13:58.580 ⇒ 00:13:59.710 Jakob Kagel: Yeah.
124 00:13:59.710 ⇒ 00:14:07.660 Nicolas Sucari: Okay, I mean, we just need to understand by comparison, 1st or by ad, but.
125 00:14:07.660 ⇒ 00:14:11.943 Jakob Kagel: Like, did you? Did you validate on the code that this is
126 00:14:13.860 ⇒ 00:14:14.480 Nicolas Sucari: No.
127 00:14:14.480 ⇒ 00:14:16.655 Jakob Kagel: Actually dollars, like
128 00:14:17.380 ⇒ 00:14:18.220 Nicolas Sucari: Nope.
129 00:14:18.220 ⇒ 00:14:23.950 Jakob Kagel: Okay, I mean, that’s what we need to validate. First, st I mean, we can pull this sure. But
130 00:14:27.980 ⇒ 00:14:28.800 Nicolas Sucari: Let me see.
131 00:14:32.230 ⇒ 00:14:33.969 Nicolas Sucari: I know I’m just like
132 00:14:34.970 ⇒ 00:14:37.889 Nicolas Sucari: struggling to understand all of that code.
133 00:14:38.070 ⇒ 00:14:39.240 Nicolas Sucari: But yeah, I think.
134 00:14:39.240 ⇒ 00:14:42.269 Jakob Kagel: Want to share your screen real quick. Maybe I’ll take a look at it.
135 00:14:42.630 ⇒ 00:14:47.179 Nicolas Sucari: Yeah, yeah, don’t worry. But I’m just yeah opening Snowflake, trying to see where’s a dead.
136 00:14:47.180 ⇒ 00:14:48.230 Jakob Kagel: Don’t worry.
137 00:14:51.120 ⇒ 00:14:52.839 Nicolas Sucari: Because I don’t know where that is.
138 00:14:55.370 ⇒ 00:15:04.660 Jakob Kagel: I mean, it’s actually like, if conversions value is like the spend, it’s what we actually need. And we have this. But what we actually need to do is do the cost
139 00:15:04.680 ⇒ 00:15:11.960 Jakob Kagel: divided by the conversions we just need to is conversions like, actually they made a purchase which it looks like. It is
140 00:15:12.080 ⇒ 00:15:13.960 Jakob Kagel: at least for Google.
141 00:15:14.110 ⇒ 00:15:16.449 Jakob Kagel: And then I’m looking at Facebook.
142 00:15:19.160 ⇒ 00:15:20.670 Nicolas Sucari: I think it’s like we are.
143 00:15:20.670 ⇒ 00:15:24.530 Jakob Kagel: It doesn’t have the same columns. Unfortunately.
144 00:15:24.650 ⇒ 00:15:29.189 Nicolas Sucari: I think we’re getting that value directly from Google.
145 00:15:30.320 ⇒ 00:15:31.180 Jakob Kagel: Right.
146 00:15:31.430 ⇒ 00:15:33.300 Nicolas Sucari: So it should be a value.
147 00:15:38.500 ⇒ 00:15:40.710 Nicolas Sucari: It should be like dollars. Yeah, I think
148 00:15:42.430 ⇒ 00:15:44.070 Nicolas Sucari: transform.
149 00:15:48.550 ⇒ 00:15:53.459 Nicolas Sucari: Because if you go to Dbt, no, wait analytics.
150 00:15:54.160 ⇒ 00:15:55.869 Nicolas Sucari: Let me see who will add.
151 00:16:02.620 ⇒ 00:16:06.599 Jakob Kagel: Yeah, Facebook ads table doesn’t have the same
152 00:16:07.410 ⇒ 00:16:08.940 Jakob Kagel: metrics.
153 00:16:15.340 ⇒ 00:16:17.890 Nicolas Sucari: But Google Google has.
154 00:16:18.120 ⇒ 00:16:22.699 Jakob Kagel: Direct mail. We have conversion date, which would be like.
155 00:16:23.350 ⇒ 00:16:26.070 Jakob Kagel: I guess everybody is converted then.
156 00:16:26.110 ⇒ 00:16:27.999 Jakob Kagel: but we don’t have
157 00:16:28.900 ⇒ 00:16:41.930 Jakob Kagel: it doesn’t look like we even have a value here, for, like the number of people like, it’s just conversion, date, campaign date. And then like a couple of other fields. But it doesn’t. Oh, email, we could do count, email, okay, yeah.
158 00:16:42.260 ⇒ 00:16:44.760 Jakob Kagel: And we have the cost. I think.
159 00:16:44.900 ⇒ 00:16:46.780 Jakob Kagel: total price. Yeah.
160 00:16:48.640 ⇒ 00:16:52.019 Jakob Kagel: I think, yeah, we could do this. I think we could do it for
161 00:16:52.150 ⇒ 00:16:59.490 Jakob Kagel: hopefully for Google, if the code, if if you’re looking at it now and then also for direct mail, we could do it
162 00:17:00.040 ⇒ 00:17:01.250 Jakob Kagel: pretty easy.
163 00:17:09.720 ⇒ 00:17:12.529 Nicolas Sucari: Or am I with 5 tran database? No.
164 00:17:22.069 ⇒ 00:17:25.949 Jakob Kagel: And I mean, that’s really like the Big 3. Honestly.
165 00:17:26.740 ⇒ 00:17:27.680 Nicolas Sucari: Okay, I have here.
166 00:17:27.680 ⇒ 00:17:30.349 Jakob Kagel: 3 is pretty solid. Yeah.
167 00:17:31.340 ⇒ 00:17:32.070 Nicolas Sucari: Yeah.
168 00:17:34.800 ⇒ 00:17:37.670 Jakob Kagel: But we just have to validate the yeah.
169 00:17:37.740 ⇒ 00:17:39.850 Jakob Kagel: the conversion value.
170 00:17:40.840 ⇒ 00:17:42.820 Jakob Kagel: Do you want to share your screen real quick?
171 00:17:42.820 ⇒ 00:17:43.400 Nicolas Sucari: Yeah.
172 00:17:43.830 ⇒ 00:17:44.730 Jakob Kagel: Let’s see.
173 00:17:46.270 ⇒ 00:17:47.330 Nicolas Sucari: Yeah, wait.
174 00:18:00.900 ⇒ 00:18:08.720 Nicolas Sucari: So I get, I think, from this table from analytics. Okay, Google Adwords row. We have here the conversion value.
175 00:18:08.780 ⇒ 00:18:11.269 Nicolas Sucari: And we have the cost per conversion, too.
176 00:18:11.750 ⇒ 00:18:12.770 Nicolas Sucari: So
177 00:18:13.550 ⇒ 00:18:21.719 Nicolas Sucari: like, I don’t know if actually, this is the cost per acquisition. If we get that, the com, if like, if we say that the conversion is the acquisition.
178 00:18:22.230 ⇒ 00:18:23.480 Nicolas Sucari: I mean that.
179 00:18:23.480 ⇒ 00:18:29.969 Jakob Kagel: Crazy, though. Go back, I mean, go back to the values I mean cost per conversion is like $300,
180 00:18:30.430 ⇒ 00:18:34.560 Jakob Kagel: and the conversion value is only 1 10. I don’t know. I mean.
181 00:18:34.560 ⇒ 00:18:36.410 Nicolas Sucari: Yeah, it seems seems awful. Yeah.
182 00:18:37.820 ⇒ 00:18:39.189 Jakob Kagel: Yeah, I’ll do that.
183 00:18:39.190 ⇒ 00:18:42.570 Nicolas Sucari: Cost here, like we have a cost column here.
184 00:18:42.570 ⇒ 00:18:43.230 Jakob Kagel: Yeah.
185 00:18:46.730 ⇒ 00:18:55.089 Jakob Kagel: I think it should be cost. And then just there’s should be. But but what we need is the actually like the logic for the table. You know what I mean.
186 00:18:55.540 ⇒ 00:18:56.920 Nicolas Sucari: Conversions.
187 00:18:57.110 ⇒ 00:19:03.579 Jakob Kagel: Because this isn’t gonna this still isn’t. Gonna this is just the staging table like this isn’t. Gonna tell us the definition. You know.
188 00:19:04.410 ⇒ 00:19:05.090 Nicolas Sucari: Yeah.
189 00:19:05.740 ⇒ 00:19:16.809 Jakob Kagel: What we need is like to be able to say like that. Conversions like the conversions column in the table is actually somebody who made a purchase. If we can do that, then it’s no problem.
190 00:19:16.970 ⇒ 00:19:21.750 Jakob Kagel: So is there a way we can just go and look at the logic for the table. Like is it in Github.
191 00:19:22.920 ⇒ 00:19:26.039 Nicolas Sucari: I don’t know. Let’s try to do it.
192 00:19:26.900 ⇒ 00:19:27.650 Jakob Kagel: Okay.
193 00:19:27.650 ⇒ 00:19:32.269 Nicolas Sucari: I don’t know what is this cost per conversion, because it’s like numbers are. It’s crazy.
194 00:19:32.270 ⇒ 00:19:41.410 Jakob Kagel: Right. I mean, we can look at the table all day. It’s not gonna help us if we don’t know the the definition for the column. So let me look. What’s the name of the table? Here, let me put in Google.
195 00:19:41.410 ⇒ 00:19:47.190 Nicolas Sucari: Google Google adwords is this one? Okay, I’m staging. Let’s go to Mars. Wait.
196 00:19:49.550 ⇒ 00:19:52.120 Jakob Kagel: Okay.
197 00:19:52.600 ⇒ 00:19:54.230 Jakob Kagel: adwords.
198 00:19:55.400 ⇒ 00:19:57.520 Jakob Kagel: Google adwords.
199 00:20:00.080 ⇒ 00:20:01.930 Jakob Kagel: parts to go.
200 00:20:16.360 ⇒ 00:20:19.990 Jakob Kagel: Okay, staging Google adwords. Sequel.
201 00:20:21.610 ⇒ 00:20:22.959 Nicolas Sucari: You see what I think.
202 00:20:24.180 ⇒ 00:20:26.299 Jakob Kagel: Doesn’t look like it, has it?
203 00:20:27.906 ⇒ 00:20:30.609 Jakob Kagel: Google adwords, raw sequel.
204 00:20:37.160 ⇒ 00:20:41.100 Jakob Kagel: add stats, dot conversions. Okay
205 00:20:42.010 ⇒ 00:20:45.449 Jakob Kagel: from source Google ad ad stats.
206 00:20:47.260 ⇒ 00:20:48.150 Jakob Kagel: Hey?
207 00:20:54.000 ⇒ 00:21:00.309 Jakob Kagel: Yeah, I think we gotta. We gotta confirm. I don’t think we have enough information here in the Github.
208 00:21:00.460 ⇒ 00:21:01.430 Nicolas Sucari: Yeah, I know. But.
209 00:21:01.430 ⇒ 00:21:04.329 Jakob Kagel: I think we gotta. I don’t know who I mean
210 00:21:05.210 ⇒ 00:21:09.930 Jakob Kagel: who the engineer is like on our side that like works with this.
211 00:21:10.130 ⇒ 00:21:17.000 Jakob Kagel: But that’s who we should. I don’t know if it’s Patrick or Ryan, or who they should be able to tell us pretty quickly
212 00:21:17.900 ⇒ 00:21:19.580 Jakob Kagel: is conversions.
213 00:21:21.030 ⇒ 00:21:23.969 Nicolas Sucari: Yeah, I’m gonna ask. I’m gonna ask Ryan, yeah.
214 00:21:24.150 ⇒ 00:21:24.760 Jakob Kagel: And.
215 00:21:25.870 ⇒ 00:21:27.700 Nicolas Sucari: And let’s see if we can
216 00:21:27.770 ⇒ 00:21:35.750 Nicolas Sucari: figure this out, because if we have the conversion value and then the cost of the campaigns, we can easily do it right.
217 00:21:35.960 ⇒ 00:21:41.110 Jakob Kagel: Yeah, no, exactly. We can, for sure. And then we should tell them like
218 00:21:41.280 ⇒ 00:21:48.110 Jakob Kagel: to also like while you, when you reach out to them, too, just as an additional. Tell them to look into like the Facebook State.
219 00:21:48.110 ⇒ 00:21:48.970 Nicolas Sucari: Yeah, yeah.
220 00:21:48.970 ⇒ 00:21:50.230 Jakob Kagel: Liver and see
221 00:21:51.450 ⇒ 00:21:57.300 Jakob Kagel: if we have like conversions there, as like something that we can bring up to the main table.
222 00:21:59.550 ⇒ 00:22:03.840 Nicolas Sucari: Yeah, because I don’t see. I don’t think we have the conversions of Facebook.
223 00:22:05.320 ⇒ 00:22:14.169 Jakob Kagel: Okay, sounds good. And then, yeah, if we confirm that, then, yeah, I can pull all the data is fine. I’ll just pull everything and send it over to her.
224 00:22:15.990 ⇒ 00:22:18.879 Jakob Kagel: but yeah, we just need them to confirm that real quick.
225 00:22:19.320 ⇒ 00:22:20.890 Nicolas Sucari: Yeah, okay.
226 00:22:22.990 ⇒ 00:22:26.335 Jakob Kagel: Sounds good, cool. Well, I’ll just be on the lookout then.
227 00:22:26.860 ⇒ 00:22:28.580 Jakob Kagel: for any updates there.
228 00:22:28.610 ⇒ 00:22:32.439 Jakob Kagel: And yeah sounds good unless there’s anything else we need to discuss.
229 00:22:33.791 ⇒ 00:22:48.040 Nicolas Sucari: I don’t think we have anything else, for now I probably we will need to work on getting that list of zip codes or list of emails from our scraper tool that we can get a list and send it to Kim.
230 00:22:48.806 ⇒ 00:22:53.309 Nicolas Sucari: For the direct mail campaign that they that she was wanting to start
231 00:22:53.850 ⇒ 00:22:54.279 Nicolas Sucari: but.
232 00:22:54.280 ⇒ 00:22:54.910 Jakob Kagel: That’s for.
233 00:22:54.910 ⇒ 00:23:05.880 Nicolas Sucari: For new customers, not for pool pros, or anything else, just for new customers that we talk. You remember we talk about around Cape Coral or North Florida, or somewhere over there.
234 00:23:07.780 ⇒ 00:23:14.099 Jakob Kagel: Yeah, of course. Yeah, just let me know exactly sort of like, specifically, if there’s anything that you need help with there, and.
235 00:23:14.100 ⇒ 00:23:29.320 Nicolas Sucari: Yeah, I need to talk to. Yeah, I need to discuss with you, Tom, on how we can extract that from old Scraper if we currently use it or not. And once we have that, I think it’s just configuration on that tool to get that list and send it to to yeah.
236 00:23:29.320 ⇒ 00:23:57.030 Jakob Kagel: Make sure like. I don’t know when we do the scraping like. Let’s make sure. Sort of like what fields we can get from them like, you know that we can hopefully sort of like easily put it into a table. In snowflake, too. I mean, I think that should be sort of like one of the main points is like, you know, we want this data. But then it’s like, we also just want to be able to put it into Snowflake and be able to join it to our existing data and query easily. So whatever.
237 00:23:57.030 ⇒ 00:23:57.690 Nicolas Sucari: Ever feel.
238 00:23:57.690 ⇒ 00:23:59.130 Jakob Kagel: His address.
239 00:23:59.470 ⇒ 00:23:59.990 Nicolas Sucari: Yeah.
240 00:23:59.990 ⇒ 00:24:09.940 Jakob Kagel: Making sure, like the address formats are like consistent or you know, email is great. If they have that. Yeah, I don’t know. We should just try.
241 00:24:09.940 ⇒ 00:24:22.339 Nicolas Sucari: And also once we get that list, we will need to remove what the ones that are already clients and try to focus on the people that we don’t have as a client yet. Yet.
242 00:24:22.340 ⇒ 00:24:23.000 Jakob Kagel: Okay.
243 00:24:23.000 ⇒ 00:24:31.759 Nicolas Sucari: Yeah, I need to discuss that with Tom. Okay, I’m gonna ask Ryan about this if he’s around, because he was also feeling a little bit sick. And Patrick was off
244 00:24:31.830 ⇒ 00:24:38.380 Nicolas Sucari: also. So yeah, I’m gonna try to see if someone can help us and yeah, and come back later. Okay.
245 00:24:38.380 ⇒ 00:24:40.589 Jakob Kagel: No worries. Sounds good. Just keep me posted.
246 00:24:40.840 ⇒ 00:24:42.669 Nicolas Sucari: Thank you, Jacob. Bye, bye.